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Associations of the fecal microbial proteome composition and proneness to diet-induced obesity

ABSTRACT: Associations of the fecal microbial proteome composition and proneness to diet-induced obesity

PROVIDER: PRJEB33328 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR3413480.fastq.gz	Fastqsanger.gz
	ERR3413490.fastq.gz	Fastqsanger.gz
	ERR3413500.fastq.gz	Fastqsanger.gz
	ERR3413510.fastq.gz	Fastqsanger.gz
	ERR3413520.fastq.gz	Fastqsanger.gz

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Associations of the Fecal Microbial Proteome Composition and Proneness to Diet-induced Obesity.

Project description:Consumption of refined high-fat, low-fiber diets promotes development of obesity and its associated consequences. Although genetics play an important role in dictating susceptibility to such obesogenic diets, mice with nearly uniform genetics exhibit marked heterogeneity in their extent of obesity in response to such diets. This suggests non-genetic determinants play a role in diet-induced obesity. Hence, we sought to identify parameters that predict, and/or correlate with, development of obesity in response to an obesogenic diet. We assayed behavior, metabolic parameters, inflammatory markers/cytokines, microbiota composition, and the fecal metaproteome, in a cohort of mice (n = 50) prior to, and the 8 weeks following, administration of an obesogenic high-fat low-fiber diet. Neither behavioral testing nor quantitation of inflammatory markers broadly predicted severity of diet-induced obesity. Although, the small subset of mice that exhibited basal elevations in serum IL-6 (n = 5) were among the more obese mice in the cohort. While fecal microbiota composition changed markedly in response to the obesogenic diet, it lacked the ability to predict which mice were relative prone or resistant to obesity. In contrast, fecal metaproteome analysis revealed functional and taxonomic differences among the proteins associated with proneness to obesity. Targeted interrogation of microbiota composition data successfully validated the taxonomic differences seen in the metaproteome. Although future work will be needed to determine the breadth of applicability of these associations to other cohorts of animals and humans, this study nonetheless highlights the potential power of gut microbial proteins to predict and perhaps impact development of obesity.

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Microbial RNAseq analysis of cecal and fecal samples collected from mice colonized with the microbiota of human twins discordant for obesity

Project description:Microbial RNAseq analysis of cecal and fecal samples collected from mice colonized with the microbiota of human twins discordant for obesity. Samples were colleted at the time of sacrifice, or 15 days after colonization from mice gavaged with uncultured or cultured fecal microbiota from the lean twins or their obese co-twins. Samples were sequenced using Illumina HiSeq technology, with 101 paired end chemistry. Comparisson of microbial gene expression between the microbiota of lean and obese twins fed a Low fat, rich in plant polysaccharide diet.

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Associations between Maternal Diet, Body Composition and Gut Microbial Ecology in Pregnancy.

Project description:Maternal body composition, gestational weight gain (GWG) and diet quality influence offspring obesity risk. While the gut microbiome is thought to play a crucial role, it is understudied in pregnancy. Using a longitudinal pregnancy cohort, maternal anthropometrics, body composition, fecal microbiome and dietary intake were assessed at 12, 24 and 36 weeks of gestation. Fecal samples (n = 101, 98 and 107, at each trimester, respectively) were utilized for microbiome analysis via 16S rRNA amplicon sequencing. Data analysis included alpha- and beta-diversity measures and assessment of compositional changes using MaAsLin2. Correlation analyses of serum metabolic and anthropometric markers were performed against bacterial abundance and predicted functional pathways. α-diversity was unaltered by pregnancy stage or maternal obesity status. Actinobacteria, Lachnospiraceae, Akkermansia, Bifidobacterium, Streptococcus and Anaerotuncus abundances were associated with gestation stage. Maternal obesity status was associated with increased abundance of Lachnospiraceae, Bilophila, Dialister and Roseburia. Maternal BMI, fat mass, triglyceride and insulin levels were positively associated with Bilophila. Correlations of bacterial abundance with diet intake showed that Ruminococcus and Paraprevotella were associated with total fat and unsaturated fatty acid intake, while Collinsella and Anaerostipes were associated with protein intake. While causal relationships remain unclear, collectively, these findings indicate pregnancy- and maternal obesity-dependent interactions between dietary factors and the maternal gut microbiome.

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Project description:Investigating alterations the intestinal microbiome in a diet induced obesity (DIO) rat model after fecal transplant from rats, which underwent Roux-Y-Gastric-Bypass surgery (RYGB). The microbiomes of the RYGB-donor rats, the DIO rats, and DIO rats after receiving the fecal transplant from the RYGB rats. As controls lean rats as well as lean, RYGB and DIO rats after antibiotics treatment were used.

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Project description:Daily sampling reveals personalized diet-microbiome associations

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Microbial RNAseq analysis of cecal and fecal samples collected from mice colonized with the microbiota of human twins discordant for obesity

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Project description:Defining the cellular factors that drive growth rate and proteome composition is essential for understanding and manipulating cellular systems. In bacteria, ribosome concentration is known to be a constraining factor of cell growth rate, while gene concentration is usually assumed not to be limiting. Here, using single-molecule tracking, quantitative single-cell microscopy, and modeling, we show that genome dilution in Escherichia coli cells arrested for DNA replication results in a decrease in the concentration of active RNA polymerases and ribosomes. The resulting sub-linear scaling of total active RNA polymerases and ribosomes with cell size leads to sub-exponential growth, even within physiological cell sizes. Cell growth rate scales proportionally with the total number of active ribosomes in a DNA concentration-dependent manner. Tandem-mass-tag mass spectrometry experiments further revealed that a decrease in DNA-to-cell-volume ratio also incrementally remodels proteome composition with cell size. Altogether, our findings indicate that genome concentration is an important driver of exponential cell growth and a global modulator of proteome composition in E. coli. Comparison with studies on eukaryotic cells suggests DNA concentration-dependent scaling principles of gene expression across domains of life.

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